Is Optimal Matching Suboptimal?

Optimal matching (OM) is a method for measuring the similarity between pairs of sequences (e.g., work histories). This article discusses two problems with optimal matching. First, the author identifies a flaw in OM ‘‘indel costs’’ and proposes a solution to this flaw. Second, the author discusses the need for benchmarks to measure the added value of OM and to test competing versions. To that end, the author conducts an empirical test of traditional OM, the alternative localized OM, and sequence comparison. The test documents the problem with traditional OM and shows that it is solved by localized OM. The test also demonstrates the value of OM and sequence comparison in examining occupational sequences; both methods capture variation beyond traditional human capital and status attainment measures, although the marginal improvements of OM over sequence comparison may not justify its computational complexity. These results point to the need for more systematic approaches to sequence analysis methods.